Precision medicine approaches in epilepsy: A systematic review of genetic markers and personalized treatment strategies

Abstract

AbstractEpilepsy is one of the most common neurological diseases globally. We conducted a systematic review of the genetic markers and personalized treatment strategies used in the precision medicine treatment of epilepsy. An exhaustive electronic search was carried out on PubMed and Google Scholar, spanning from inception up to June 2023 on epilepsy and biomarkers. A total of 45 articles from PubMed and 19 articles from Google Scholar were imported and screened based on studies that focused primarily on genetic markers and precision methods for epilepsy subtyping, treatment strategies, outcomes, and adverse effects. Reviews and studies not in English were excluded. Full‐text data extraction, coding, and analysis were carried out with Microsoft Excel. For the risk of bias assessment of the final included studies, the Critical Appraisal Skills Program checklist was used. A total of 19 studies were analyzed in the review. The SLC35A2 gene saw a reduction in seizure frequency with d‐galactose treatment while the KCNQ2 gene saw improvement with phenytoin, carbamazepine, and retigabine. GRIN2D gene saw varying improvements with memantine. KCNT1 gene saw improvement with only a combination of quinidine and topiramate, quinidine was not useful when used alone. Other studies involved the identification of different markers using gene and exome sequencing. These studies collectively provide a diverse range of insights into epilepsy, with variations in study design, sample size, age groups, and diagnostic criteria, highlighting the multifaceted nature of epilepsy research. These studies contribute to our understanding of epilepsy diagnosis and management in different clinical settings, however, there were some limitations such as QT prolongation was observed with specific medications and participant heterogeneity. Small sample sizes reduced statistical power and brief durations of studies limited their ability for long‐term analysis. Although most studies had a low risk of bias, two studies demonstrated some reporting bias. Fianlly, the absence of biomarkers is a limitation that impedes the study's capacity to explore underlying biological mechanisms.